Stanford University HIV Drug Resistance Database - A curated public database designed to represent, store, and analyze the divergent forms of data underlying HIV drug resistance.

Stanford HIVdb FAQ: Questions and Answers

Last updated on May 30, 2008
Comments and suggestions to HIVDB
If I don't find it here, does that mean that it doesn't exist?

This FAQ is written as the need arises, and thus it will continue to grow. This provides a convenient mechanism for responding to common questions that we receive.

Can I submit questions that I think should be part of this FAQ?

Please do. We welcome questions for the Stanford HIVdb FAQ. The questions most likely to make it into the FAQ are those that will benefit a large proportion of Stanford HIVdb users. In addition, if you find answers that are incorrect or ambiguous, please let us know!

How do I cite Stanford HIVdb?

Soo-Yon Rhee, Matthew J. Gonzales, Rami Kantor, Bradley J. Betts, Jaideep Ravela, and Robert W. Shafer (2003) Human immunodeficiency virus reverse transcriptase and protease sequence database. Nucleic Acids Research, 31(1), 298-303.

How does Stanford HIVdb define mutations?

Mutations are defined as any difference from the consensus B amino acid sequence. Links to the consensus B amino acid sequences for protease, RT, and integrase can be found here.

How does Stanford HIVdb indicate mutations?

A shorthand consisting of the consensus B amino acid followed by the amino acid position followed by the amino acid in a sequence is used. Amino acids are indicated using the one letter amino acid code, The presence of more than one amino acid following the position number indicates that there is a mixture of genotypes with different amino acids at this position. We also use some symbols in addition to one-letter amino acid codes; # for an amino acid insertion; ~ for an amino acid deletion; X for a mixtures of four and more amino acids; * for a stop codon; a dot for an unknown amino acid. The partcular gene in which the mutation is present - RT, protease, or integrase - should be clear from the context of the web page.

Why is the subtype B consensus sequence used rather than a particular isolate, the consensus sequence for a different subtype, or the consensus sequence for Group M sequences?

This is a commonly adopted convention that dates back to the late 1980s and early 1990s when subtype B viruses were the most common viruses in the U.S. and Europe. Using a different subtype of a group M consensus would cause too much confusion at this time. Using a particular isolate would also be confusing as nearly every common laboratory isolate has one or more unusual mutations that would always need to be noted. For example, the common laboratory strain HXB2 has a rare I3V mutation in protease. Therefore, if HXB2 was used for the consensus, nearly every sequence would have a V3I mutation in protease.

What are the currently available antiretroviral drugs(ARVs) and drug classes?

Currently available antiretroviral drugs (ARVs) belong to one of six different drug classes: (i) Nucleoside reverse transcriptase (RT) inhibitors (NRTIs), (ii) Non-nucleoside RT inhibitors (NNRTIs), (iii) Protease inhibitors (PIs), (iv) Integrase inhibitors (INIs), (v) Fusion inhibitors, and (vi) CCR5 inhibitors. There is currently one FDA-licensed INI, one FDA-licensed fusion inhibitor, and one FDA-licensed CCR5 inhibitor. However, there are additional INIs and CCR5 inhibitors in advanced clinical trials. A complete listing of all approved ARVs, their drug class (or mechanism of action), date of FDA licensing, generic name, trade name, and common abbreviations can be found here (I have a page with a complete table).

Which mutations are considered drug resistance mutations?

The association between a mutation and drug resistance is based on three types of correlations around which much of the database is organized: Genotype-treatment correlations, Genotype-phenotype correlations, Genotype-clinical outcome correlations. Genotype-treatment correlations pertain to whether the mutation is selected by antiretroviral drug therapy in vitro and/or in vivo. Genotype-phenotype correlations pertain to whether a mutation reduces or contributes to reduced drug susceptibility in vitro. Genotype-clinical outcome correlations represent statistical associations between the presence of a mutation prior to the start of a new antiretroviral treatment regimen. These associations, however, must be controlled by many factors such as the past treatment of a patient, the baseline virus level, and the complete make up of the regimen used for salvage therapy.

However, the literature on HIV drug resistance mutations is vast and many mutations have been linked to drug resistance by one of the three criteria described in the preceding paragraph. The strength of supporting evidence for different mutations Is also highly variable. Some mutations fulfill all three criteria solidly; others fulfill only one or two criteria. The association of other mutations with antiretroviral treatment, reduced in vitro susceptibility, or decreased response to ARV therapy is supported only by the flimsiest of statistical evidence. The need for adequate data is one of the primary rationales for this database. However, when such data have been lacking, a certain amount of judgment has been used to determine which mutations are categorized as drug-resistance mutations.

Do any drug resistance mutations reduce susceptibility to drugs belonging to more than one drug class?

The NRTIs and NNRTIs inhibit the same HIV-1 protein - the RT enzyme. In contrast, the PIs inhibit the protease enzyme, the INIs inhibit the integrase enzyme, the fusion inhibitors inhibit the gp41 transmembrane envelope (Env) protein, and the CCR5 inhibitors disrupt the mechanism by which the gp120 surface Env protein binds to CCR5. Even though the NRTIs and NNRTIs inhibit the same protein, there is surprisingly little evidence for cross-resistance between these drug classes (i.e. mutations that reduce susceptibility to one or more drugs of each drug class). In fact, several mutations that reduce NRTI susceptibility increase NNRTI susceptibility and several mutations that reduce NNRTI susceptibility increase NRTI susceptibility. This "antagonism" between many NRTI and NNRTI resistance mutations may be responsible from the "synergism" of NRTI and NNRTI drug combinations.

However, in the past 2-3 years, several RT mutations have been identified that are associated with both NRTI and NNRTI therapy and possibly contribute to reduced susceptibility to one or more ARVs of each class. The two mutations for which there is the most convincing evidence are N348I and H221Y but further work is required to quantify the effect that these mutations have on NRTIs and NNRTIs. N348I is in a part of the RT that is not routinely sequenced because most genotypic resistance assays rarely sequence beyond positions 240 to 340. The effect of N348I has also not been tested by the PhenoSense assay because this assay tests uses patient-derived amplicons that include only positions 1 to 316. H221Y generally occurs only in combination with multiple NRTI mutations and although it occurs more commonly in viruses from patients receiving NRTIs + NNRTIs (NNRTIs are rarely administered without NRTIs), there are no phenotypic data available yet demonstrating that H221Y decreases susceptibility to any of the NNRTIs.

Although fusion inhibitors and CCR5 inhibitors both target Env, they each target different parts of Env as noted above. Resistance to fusion inhibitors is caused nearly entirely by mutations betweem positions 37 to 45 of gp41 whereas resistance to CCR5 inhibitors is caused primarily by gp120 mutations concentrated largely in the V3 loop. However, the mechanism of CCR5 inhibitor resistance is complex and there has been one report showing that the genetic context of gp41 may rarely influence CCR5 inhibitor susceptibility.

Why are some drug-resistance mutations called "Major" and others called "Minor"?

So many mutations have been associated with decreased HIV-1 susceptibility by the criteria described above that it has become common to sub-classify mutations associated with each of the different drug classes. The most common sub-classifications have divided mutations into "Major" vs "Minor" or "Primary" vs "Secondary" categories. Specific criteria for these sub-classifications have never been established and existing classification schemes have been developed on an ad hoc basis. This is not surprising considering that there is not even always a consensus on what constitutes a drug resistance mutation.

The following characteristics of a drug-resistance mutation have influenced its classification: (i) Effect on in vitro drug susceptibility - mutations that by themselves reduce susceptibility to one or more drugs are generally classified as "Major". In contrast, mutations with little or no demonstrated effect on susceptibility are usually classified as accessory or "Minor". The term accessory is used either because these mutations usually reduce susceptibility only in combination with a major mutation or increase the replication fitness of viruses containing major drug resistance mutations; (ii) Frequency of the mutation among persons experiencing virological failure - mutations that occur commonly during virological failure are more likely to be classified as "Major". In contrast, rare mutations or those that usually occur only after other drug-resistance mutations are more likely to be classified as "Minor"; (iii) Extent of polymorphism among untreated persons - mutations that occur commonly in untreated patients as naturally occurring variants (in contrast to transmitted drug-resistant variants) are more likely to be classified as "Minor". Several naturally occurring variants cause slight reductions in drug susceptibility. Fortunately, none cause large reductions in drug susceptibility; (iv) Location of the mutation within the targeted protein - mutations at structurally important and conserved parts of a protein are more likely to be considered "Major". These mutations, also often cause greater reductions in drug susceptibility.

The rationale for the sub-classification can be found in the tabular summaries present on the website (link) and on the printable two-page PDF summary (link). The relative importance of different mutations are also reflected in the individual drug summaries, the weighted penalties for the mutations, and the comments for each of the mutations.

Which mutations are defined as Major and Minor drug resistance mutations (DRMs)?

A complete listing of which mutations are classified as Major and which are classified as Minor for the NRTIs, NNRTIs, PIs, and INIs can be found here: Protease Inhibitors (PIs) associated DRMs, Nucleoside RT inhibitors (NRTIs) associated DRMs, Non-nucleoside RT inhibitors (NNRTIs) associated DRMs and Integrase inhibitors (INIs) associated DRMs. To learn about an individual drug resistance mutation, please begin with these links: PIs associated DRMs, NRTIs associated DRMs, NNRTIs associated DRMs, INIs associated DRMs.

As the criteria for classification are somewhat subjective, it is likely that there will be changes over time that will be recorded at this page.

How does Stanford HIVdb classify mutations?

The HIV Drug Resistance Database uses several different classification schemes. The HIVdb program and several of the query pages (such as detailed treatment queries, detailed mutation queries, advanced queries, detailed phenotype queries, and reference page) use a 3-way classification scheme that classifies protease mutations into "Major", "Minor", and "Other", RT mutations into "NRTI", "NNRTI", and "Other" and integrase mutations into "Major", "Minor" and "Other". According to this scheme, "NRTI" and "NNRTI" mutations cannot be further subdivided without the output becoming too unwieldy requiring 5 rather than 3 categories. Moreover, the original sub-classification of mutations into "Major" and "Minor" categories began with the PIs and so most HIV drug resistance researchers and clinicians are comfortable with this classification scheme.

Other also includes Unusual mutations Of note, many of the mutations classified by the Database as "Other" (meaning that they generally are not recognized as being "Major" or "Minor") are known to occur more commonly in patients receiving ARVs than among ARV-naïve persons. These mutations generally fit into one of two categories: (i) Mutations that have a known weak association with reduced drug susceptibility but that occur commonly in viruses from ARV-naïve persons. For example, protease mutations at positions 20, 36, 63, 77, and 93 were among the first mutations reported to be associated with decreased PI susceptibility. However, mutations at these positions occur so commonly in untreated persons (e.g. at a prevalence of between 20% to >90% depending on the subtype), that classifying these mutations as drug-resistance mutations would mean that nearly ever protease isolate would contain one or more drug-resistance mutation. Fortunately, none of these mutations appear to reduce drug susceptibility or interfere with clinical response to therapy by themselves. (ii) Mutations that may have a stronger association with ARV therapy but which are not common and for which insufficient data exist in the published literature to classify them as drug-resistance mutations. A complete list of mutations found in a protease sequence is classified into 3-way or 4-way. 3-way classification includes PIMajorDRMs, PIMinorDRMs, NonDRMs. 4-way classification includes PIMajorDRMs, PIMinorDRMs, Polys(Polymorphism), UnusualMuts(unusual or atypical mutations). NonDRMs are the mutations that are not classified as PIMajorDRMs or PIMinorDRMs. A list of NonDRMs further breaks down to Polys and UnusualMuts. Polys are the mutations that are not classified as PIMajorDRMs, PIMinorDRMs, or UnusualMuts. UnusualMuts are the mutations that occure <0.5% in untreated and <0.1% in treated persons in Stanford HIVdb. 3-way classification is used for returning a query results such as detailed treatment queries, detailed mutation queries, advanced queries, detailed phenotype queries, and reference page on the Stanford HIVdb web site. 4-way classification is used for returning detailed information on an isolate on the Stanford HIVdb web site when users click on an isolate link provided on query results pages. The list of PIMajorDRMs is used when users choose an option for excluding MajorDRMs on mutation query page and detailed phenotype query page.

Integrase mutations are classified in the same way that protease mutations are classified.

RT mutations are classified into 3-way or 6-way. 3-way classification includes NRTIDRMs, NNRTIDRMs, NonDRMs. NRTIDRMs include NRTIMajorDRMs and NRTIMinorDRMs. NNRTIDRMs include NNRTIMajorDRMs and NNRTIMinorDRMs. NonDRMs include mutations that are other than NRTIDRMs and NNRTIDRMs. 6-way classification includes NRTIMajorDRMs, NRTIMinorDRMs, NNRTIMajorDRMs, NNRTIMinorDRMs, Polys, UnusualMuts. Polys are the mutations that are not classified as NRTIDRMs, NNRTIDRMs, or UnusualMuts. UnusualMuts are the mutations that occure <0.5% in untreated and <0.1% in treated persons in Stanford HIVdb. 3-way classification is used for returning a query results such as detailed treatment queries, detailed mutation queries, advanced queries, and reference page on the main web site. A list of NRTIMajorDRMs, NRTIMinorDRMs, NNRTIMajorDRMs, NNRTIMinorDRMs and NonDRMs is used for returning a query results such as detailed phenotype queries. 6-way classification is used for returning detailed information on an isolate on the main web site when users click on an isolate link provided on query results pages. The list of NRTIMajorDRMs is used when users choose a NRTI mutation with an option for excluding MajorDRMs on mutation query page and detailed phenotype query page. The list of NNRTIMajorDRMs is used when users choose a NNRTI mutation with an option for excluding MajorDRMs on mutation query page and detailed phenotype query page.

Is there a detailed description of the Genotypic Resistance Interpretation program?

Yes, a detailed description of the HIVdb Program: Genotypic Resistance Interpretation Algorithm program is available in the Release Notes.

Are changes made to the Genotypic Resistance Interpretation algorithm documented?

Yes, the scoring tables, comments, and programs are frequently updated and these updates are tracked in the Updates page. Current and previous versions linking to the specific improvements are available since January 2003.

What other Genotypic Resistance Interpretation algorithms are available besides HIVdb's? Can I specify my own?

HIValg compares HIVdb results to those of 2 other algorithms: i. Rega Institute (rules), and ii. Agence Nationale de Recherches sur le SIDA (ANRS rules). HIValg also allows users to interpret sequences using any algorithm created using the Algorithm Specification Interface (ASI). Users can create their own algorithm and then upload it with their sequence.

We are looking for a way to automate the retrieval of data from your web application. Since your database is continually being updated, we would like to have the capability of matching up the data on a periodic basis?

A web service (known as Sierra) has been created to allow users to take advantage of HIVdb Genotypic Resistance Interpretation algorithms programmatically. Sierra enables other computers to obtain the latest Stanford HIV Drug Resistance Algorithm scores, comments, and inferred levels of resistance to 17 FDA-approved protease and RT inhibitors.

What is a B,D,H,V,N QA Problem in the section Sequence Quality Assessment of the Interpretation report? What are the blue and red lines in the graph?

As part of our quality control analysis the report lists positions containing highly ambiguous nucleotides: N (cannot distinguish between A,C,G, or T), B (contains a combination of C, G, and T), D (contains a combination of A, G, and T), H (contains a combination of A, C, T), and V (contains a combination of A, C, and G). Whereas mixtures of two nucleotides occur commonly and do not reflect sequencing artifact, the presence of mixtures with three or more nucleotides at the same position occurs rarely in high quality sequences.
For instance if codon 181 was "KDT" and kept in mind that:

  • K means that G and T were observed, and
  • D means that A, G, and T were observed.
you would realize that there are 6 amino acid possibilities:
  • GAT => D
  • GGT => G
  • GTT => V
  • TAT => Y
  • TGT => C
  • TTT => F
When our program encounters a complex mixture that breaks down into more than 4 possibilities, we assign an "X" which means uninterpretable and receives no score. The decision to assign an X in such circumstances is a judgement call. Otherwise any highly ambiguous set of nucleotides at a drug-resistance position would trigger a mutation. Of note, such complex mixtures are extremely rare.

The summary figure accompanying the quality control analysis contains blue lines for each difference from consensus B and red lines for each problem position.

What happens when the submitted sequence has a reading frame-shift?

The summary data section of the report indicates reading frame-shifts. Following is an example of what would happen if there was an extra single base in RT codon 29.

There is a reading frame shift! Please examine the sequence carefully. The presence of a reading frame shift (insertions or deletions that are not multiples of 3 NA) suggests the possibility of a sequencing error. Reading frame shifts in this sequence are shown below. A region of the underlying raw alignment text on either side of the reading frame shift is also shown.

  1. Shift of length 1 nucleic acids at codon 29 in RT
                  . :::  .  . .... .. - ..:::     .  . .. .
                  lnTrpProLeuThrGluGlu LysIleLysAlaLeuValGl